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The use of a sequence of experiments, where the design of each may depend on the results of previous experiments, including the possible decision to stop experimenting, is within the scope of sequential analysis, a field that was pioneered [12] by Abraham Wald in the context of sequential tests of statistical hypotheses. [13]
In the design of experiments, optimal experimental designs (or optimum designs [2]) are a class of experimental designs that are optimal with respect to some statistical criterion. The creation of this field of statistics has been credited to Danish statistician Kirstine Smith .
The Design of Experiments. Author: Fisher, RA Publication data: 1935, Oliver and Boyd, Edinburgh Description: The first textbook on experimental design Importance: Influence [12] [13] [14] The Design and Analysis of Experiments. Author: Oscar Kempthorne Publication data: 1950, John Wiley & Sons, New York (Reprinted with corrections in 1979 by ...
Mixture experiments are discussed in many books on the design of experiments, and in the response-surface methodology textbooks of Box and Draper and of Atkinson, Donev and Tobias. An extensive discussion and survey appears in the advanced textbook by John Cornell.
Ronald Fisher. Statistical Methods for Research Workers is a classic book on statistics, written by the statistician R. A. Fisher.It is considered by some [who?] to be one of the 20th century's most influential books on statistical methods, together with his The Design of Experiments (1935).
In the design of experiments, completely randomized designs are for studying the effects of one primary factor without the need to take other nuisance variables into account. This article describes completely randomized designs that have one primary factor.
The Design of Experiments is a 1935 book by the English statistician Ronald Fisher about the design of experiments and is considered a foundational work in experimental design. [2] [3] [4] Among other contributions, the book introduced the concept of the null hypothesis in the context of the lady tasting tea experiment. [5]
Bayesian experimental design provides a general probability-theoretical framework from which other theories on experimental design can be derived. It is based on Bayesian inference to interpret the observations/data acquired during the experiment. This allows accounting for both any prior knowledge on the parameters to be determined as well as ...